CN115310860A - Method for comprehensively evaluating quality of fresh litchi - Google Patents
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Abstract
The invention discloses a method for comprehensively evaluating the quality of fresh litchi, which comprises the following steps: determining a fresh edible litchi sample according to the production area and variety of the fresh edible litchi; establishing a three-level quality evaluation system of fresh litchi; measuring an index value x of each group of quality evaluation indexes, and carrying out data standardization on the index value x: constructing a quality evaluation index weight matrix W of each quality evaluation category; calculating the score value H of each quality evaluation category; carrying out data standardization on the score value H of each quality evaluation category; constructing a quality evaluation category weight matrix A of each fresh litchi sample; calculating the comprehensive score Y of each quality evaluation target layer according to the weight matrix A and the score value H; and determining the quality grades of the m fresh litchi samples according to the comprehensive score Y. The method for comprehensively evaluating the quality of the fresh litchi has statistically objective basis, unified standard and systematic synthesis, and can provide objective and comprehensive judgment standard for the quality of the fresh litchi.
Description
Technical Field
The invention belongs to the technical field of food, and particularly discloses a method for comprehensively evaluating the quality of fresh litchi.
Background
Currently, agriculture in China is accelerating to enter a new stage of meeting nutritional and health requirements, agricultural production is transformed from survival type food supply guarantee to health type meeting nutritional requirements, food supply is transformed from meeting general public type food consumption requirements to meeting personalized customized type food consumption requirements. The "national quality of agriculture strategic planning (2018-2022) published in 2018 also explicitly puts forward the requirement of" high product quality ". The supply quantity of high-quality agricultural products is greatly increased, and better taste, better quality and more balanced nutrition are required. The litchi is a beautiful name of the Lingnan Jiaguo, is the first fruit in the south of China, has beautiful appearance, white meat and rich nutrition, is the first choice for fruit consumption in summer, especially changes the attention of consumers from the past existence to the present quality under the current large background, and the litchi with good flavor and quality becomes the first choice for consumers, especially for high-income people. Therefore, how to evaluate the high-quality fresh-eating litchi becomes the problem to be solved urgently at present.
Disclosure of Invention
In order to solve the problems in the prior art, the method for comprehensively evaluating the quality of the fresh litchi provides objective, scientific and comprehensive theoretical support for evaluating the quality of the fresh litchi.
The above purpose is realized by the following technical scheme:
a method for comprehensively evaluating the quality of fresh litchi comprises the following steps:
step 1: determining fresh litchi samples according to the production area and variety of fresh litchi, wherein the number of the fresh litchi samples is m, m =1,2,3,4,5 \8230;
step 2: establishing a three-level quality evaluation system of fresh litchi, wherein the three-level index evaluation system of the comprehensive evaluation of the quality of the fresh litchi comprises a quality evaluation index layer, a quality evaluation category layer and a quality evaluation target layer from bottom to top, the quality evaluation category layer comprises h quality evaluation categories, the quality evaluation index layer comprises h groups of quality evaluation indexes, the number of each group of quality evaluation indexes is n, each quality evaluation category comprises a group of quality evaluation indexes, the quality evaluation target layer is m fresh litchi samples, h =1,2,3,4,5 \8230, 8230, n =1,2,3,4,5 \8230, 8230;
and step 3: measuring the index value x of each group of quality evaluation indexes, and carrying out data standardization on the index value x to obtain a quality evaluation index standard value z of each group of quality evaluation indexes:
and 4, step 4: calculating the contribution weight w of each group of quality evaluation indexes q Constructing a quality evaluation index weight matrix W for each quality evaluation category g Calculating the contribution weight a of h quality evaluation categories g ；
And 5: calculating a score value H for each quality evaluation category p-g ；
Step 6: according to the contribution weight a g And a score value H p-g Calculating the comprehensive score Y of each fresh litchi sample p ；
And 7: according to a composite score Y p Comparing and sequencing the quality of the m fresh litchi samples, determining the quality grade of the m fresh litchi samples, and comprehensively scoring Y p The larger the sample, the better the quality of the fresh litchi sample.
According to one embodiment of the present invention, the quality evaluation category of the quality evaluation category layer includes, but is not limited to, taste quality, processing quality, nutritional quality, commodity quality, storage and transportation quality.
According to one embodiment of the present invention, the quality evaluation index of the taste quality includes, but is not limited to, soluble solids, sugar-acid ratio, pH, total acid, organic acid; the quality evaluation indexes of the processing quality include, but are not limited to, juice yield, moisture, nuclear weight and ash content; the quality evaluation indexes of the nutritional quality include, but are not limited to, total sugar, vitamins, protein, amino acids, fat; the quality evaluation indexes of the commodity quality include but are not limited to edibility, single fruit weight, peel brightness and defective fruit; the storage and transportation quality includes, but is not limited to, preservation performance during storage, preservation performance during transportation, and preservation performance during shelf life.
According to one embodiment of the present invention, step 3 comprises:
step 31: measuring the index value x of each quality evaluation index group, performing consistency processing on the index value x of each quality evaluation index group,
classifying the n quality evaluation indexes into an intermediate index, an interval index and an ultra-small index according to the preferred values of the quality evaluation indexes, and then respectively converting the intermediate index, the interval index and the ultra-small index into an ultra-large index, wherein,
the intermediate index is converted into an extremely large index according to the following formula:
in the formula, x m ' represents the index value, x, of the mth fresh litchi sample after the conversion of a certain quality evaluation index m Indicating the index value of a certain quality evaluation index of the mth fresh litchi sample before transformation, X indicating a data set containing all measured values of the quality evaluation index, and X best Representing the best value in the data set X,
the interval index is converted into an extremely large index according to the following formula:
m = max { a-mix (X), max (X) -b } formula (3)
Where a, b represent the lower and upper bounds of the optimal interval [ a, b ] in the data set X, M represents the distance from the optimal interval,
the ultra-small index is converted into the ultra-large index according to the following formula:
step 32: carrying out dimensionless processing on the data obtained by the consistency processing index value x to obtain a quality evaluation index standard value z of each group of quality evaluation indexes;
in the formula z m The standard value after the m-th quality evaluation index was normalized is shown.
According to one embodiment of the invention, step 4 comprises:
step 41: respectively selecting the relative importance of n quality evaluation indexes and h quality evaluation categories according to a scaling method, and respectively constructing a quality evaluation index judgment matrix B for each group of quality evaluation indexes g For each quality evaluation category, a quality evaluation category judgment matrix A is constructed g Calculating a quality evaluation index judgment matrix B g And a quality evaluation category judgment matrix A g Maximum eigenvalue λ of max And a consistency ratio CR, performing consistency check,
quality evaluation index judgment matrix B g Comprises the following steps:
in the formula, the element b 21 Is a quality evaluation index B 2 Compared with the quality evaluation index B 1 The importance of (c); n is the order of the judgment matrix, namely the number of quality evaluation indexes of each group, n =1,2,3 \8230,
the calculation formula for the consistency check is as follows:
wherein CI is a consistency index, RI is an average random consistency index,
comparing the consistency ratio CR with 0.1, and if CR is less than 0.1, passing consistency check; if CR is more than or equal to 0.1, the consistency test is not passed,
step 42: if the quality evaluation index judgment matrix Bg passes consistency check, calculating a quality evaluation index judgment matrix B g Maximum eigenvector and contribution weight w q Calculating a quality evaluation category judgment matrix A g Maximum eigenvector and contribution weight ofa g Then according to the contribution weight w q Constructing a quality evaluation index weight matrix W g (ii) a If the quality evaluation index judges the matrix B g If the consistency check is not passed, the step 41 is repeated until the quality evaluation index judgment matrix B is reached g And a quality evaluation category judgment matrix A g Through the consistency check, the method can check the consistency,
contribution weight w q The calculation formula is as follows:
in the formula, the contribution weight w q Represents the contribution weight of the q-th quality evaluation index, q =1,2.. N,
contribution weight a g Is calculated and the contribution weight w q In the same way, the first and second,
quality evaluation index weight matrix W g Comprises the following steps:
in the formula, a quality evaluation index weight matrix W g A weight matrix representing a g-th set of quality assessment indicators, g =1,2.
According to one embodiment of the invention, step 5 comprises:
step 51: constructing a quality evaluation index initial evaluation matrix E according to the standard value x of each group of quality evaluation indexes g ，
Initial evaluation matrix E of quality evaluation index g Comprises the following steps:
in the formula, an initial evaluation matrix E of quality evaluation indexes g Representing the initial evaluation matrix of the g group quality evaluation indexes; m represents the number of fresh litchi samples, and n represents the number of quality evaluation indexes; element e mn Indicating the mth fresh litchi sampleQuality evaluation index standard value x of the n indexes mn ，
Step 52: initial evaluation matrix E combined with quality evaluation indexes g And a quality evaluation index weight matrix W g Constructing a quality evaluation index weighted evaluation matrix K g ，
Quality evaluation index weighted evaluation matrix K g The calculation formula of (2) is as follows:
in the formula, K g A weighted evaluation matrix representing the g-th group of quality evaluation indexes, m represents the number of fresh litchi samples, n represents the number of the quality evaluation indexes,
step 53: determining a quality evaluation index weighted evaluation matrix K g Of (2) an optimal solution K q + And worst solution K q - Calculating the p-th fresh litchi sample and the optimal solution K q + Euclidean distance k of q + Calculating the p-th fresh litchi sample and the worst solution K q - Euclidean distance k of q - ，p＝1，2，3....m，q＝1，2，3...n，
K g + ＝[k 1 + ，k 2 + ，....，k n + ]＝[max(k 11 ，k 21 ，...，k m1 )，max(k 12 ，k 22 ，...，k m2 )，...，max(k 1n ，k 2n ，...，k mn )]Formula (13)
K g - ＝[k 1 - ，k 2 - ，...，k n - ]＝[min(k 11 ，k 21 ，...，k m1 )，min(k 12 ，k 22 ，...，k m2 )，...，min(k 1n ，k 2n ，...，k mn )]Formula (14)
Optimal solution K q + Weighting the quality evaluation index by an evaluation matrix K g Of medium m fresh litchi samplesSet of maximum values of corresponding elements under n quality evaluation indexes, worst solution K q - Weighting the quality evaluation index by an evaluation matrix K g The minimum value set of the n quality evaluation indexes of the medium m fresh eating litchi samples,
in the formula, k pq A weighting standard value, k, of the q-th quality evaluation index of the p-th fresh litchi sample pq - A weighting standard value, k, of the q-th quality evaluation index of the p-th fresh litchi sample q + 、k q - Respectively represents K q + And K q - The maximum and minimum values of the qth index in the m samples, p =1,2,3 \ 8230m, q =1,2,3 \ 8230n,
step 54: according to Euclidean distance k p + 、k p - Calculating the score value H of the quality evaluation category p-g ，
In the formula, H p-g The score values representing the g-th quality assessment category of the p-th fresh litchi sample, p =1,2,3.. M, g =1,2,3.. H.
According to one embodiment of the invention, step 6 comprises:
calculating a composite score Y according to the following calculation formula p ，
In the formula Y p Represents the integration of the p-th fresh litchi sampleScore, p =1,2,3.
Drawings
FIG. 1 is a schematic diagram of a three-level quality evaluation system in the comprehensive evaluation method for fresh litchi quality.
FIG. 2 is a flow chart of the method for comprehensively evaluating the quality of fresh litchi.
Detailed Description
The present invention will be described in detail below with reference to the drawings and examples.
According to the method for comprehensively evaluating the quality of the fresh litchi, the quality of the fresh litchi is sorted and compared by adopting a comprehensive evaluation model, so that the quality grade of the fresh litchi is obtained, and a scientific and objective basis is provided for selecting the high-quality fresh litchi.
The method for comprehensively evaluating the quality of the fresh litchi comprises the following steps:
step 1: according to the production area and variety of the fresh litchi, fresh litchi samples are determined, wherein the number of the fresh litchi samples is m, m =1,2,3,4,5, 8230, 8230and the method is suitable for the fresh litchi samples. Selecting fresh litchi to be selected, wherein the fresh litchi cannot be immature or rotten but cannot be eaten fresh, and the appearance of the fresh litchi can be poor but cannot influence eating. To specifically explain how the comprehensive evaluation method for the quality of fresh litchi is performed, the number m =12 of fresh litchi samples in the specific embodiment.
Step 2: a three-level quality evaluation system of fresh litchi is established, the three-level index evaluation system of the comprehensive evaluation of the quality of fresh litchi comprises a quality evaluation index layer, a quality evaluation category layer and a quality evaluation target layer from bottom to top, the quality evaluation category layer comprises h quality evaluation categories, the quality evaluation index layer comprises h groups of quality evaluation indexes, the number of each group of quality evaluation indexes is n, each quality evaluation category comprises a group of quality evaluation indexes, the quality evaluation target layer is m fresh litchi samples, h =1,2,3,4,5 \8230, 8230, n =1,2,3,4,5 \8230, 8230and the 8230are combined.
The quality evaluation category of the quality evaluation category layer includes, but is not limited to, taste quality, processing quality, nutritional quality, commodity quality, and storage and transportation quality. These quality evaluation categories are selected according to the quality required by fresh litchi in terms of picking, transportation, storage, eating, etc., and according to evaluation criteria and requirement differences.
The quality evaluation indexes of the taste quality include, but are not limited to, soluble solids, sugar-acid ratio, pH, total acid, and organic acid; the quality evaluation indexes of the processing quality include but are not limited to juice yield, moisture, nuclear weight and ash content; the quality evaluation indexes of the nutritional quality include, but are not limited to, total sugar, vitamins, protein, amino acids, fat; the quality evaluation indexes of the commodity quality include but are not limited to edibility, single fruit weight, peel brightness and defective fruit; the storage and transportation quality includes, but is not limited to, preservation performance during storage, preservation performance during transportation, and preservation performance during shelf life.
In the specific embodiment, referring to fig. 1, the number of fresh litchi samples in the quality evaluation target layer is 12, and the evaluation categories corresponding to the 12 samples include 4, which are the taste quality, the processing quality, the nutritional quality, and the commodity quality. Each quality evaluation category comprises 3 quality evaluation indexes, specifically, the quality evaluation indexes of the taste quality comprise but are not limited to soluble solid, sugar-acid ratio and total acid; the quality evaluation indexes of the processing quality include but are not limited to juice yield, moisture and nuclear weight; the quality evaluation indexes of the nutritional quality include, but are not limited to, total sugar, vitamins, and proteins; the quality evaluation indexes of the commodity quality include but are not limited to the edibility, the single fruit weight and the peel brightness.
As can be seen from fig. 1, each quality evaluation category is determined by 3 quality evaluation indexes, each quality evaluation index can be directly measured by a corresponding instrument, and a corresponding index value x is calculated. For example, soluble solids can be calculated by a brix refractometer measurement. The score value H of each quality evaluation category can be indirectly obtained through index values of 3 quality evaluation indexes. Therefore, the determination of each quality evaluation category is independent of each other. Moreover, each fresh litchi sample is determined by four quality evaluation categories. The comprehensive score Y of each fresh litchi can be obtained by calculating the score value H of the corresponding quality evaluation category, so that the quality of each fresh litchi is judged independently. The setting of the comprehensive quality evaluation system is from top to bottom, but the calculation is from bottom to top.
And step 3: and measuring the index value x of each group of quality evaluation indexes, and carrying out data standardization on the index value x to obtain a quality evaluation index standard value z of each group of quality evaluation indexes.
First, the index value of the quality evaluation index of fresh litchi was measured by an appropriate measuring instrument, as shown in table 1.
TABLE 1 index value x of evaluation index for quality of fresh litchi
Then, the data normalization of the index value x includes steps 31 and 32.
Step 31 proceeds as follows: measuring the index value x of each group of quality evaluation indexes, performing consistency processing on the index value x of each group of quality evaluation indexes,
the n quality evaluation indexes are classified into an intermediate index, an interval index and an ultra-small index according to the optimal values of the quality evaluation indexes, and then the intermediate index, the interval index and the ultra-small index are respectively converted into an ultra-large index x'. In the method for comprehensively evaluating the quality of the fresh litchi, various index values of the quality evaluation indexes of the fresh litchi are classified as follows:
in the method for comprehensively evaluating the quality of the fresh litchi, the sugar-acid ratio adopts an interval index, the nuclear weight adopts a very small index, and other indexes adopt a very large index. Wherein x is m′ An index value x representing a consistent quality evaluation index of the mth fresh litchi sample m And the index value represents a certain quality evaluation index of the mth fresh litchi sample.
The four most common indicators:
| index name | Index characteristics |
| Very large scale (benefit type) index | The larger the size, the better the quality |
| Very small (cost-effective) index | The smaller the size, the better the |
| Intermediate type index | The closer to a certain value, the better |
| Interval type index | Preferably falling within a certain interval |
The intermediate index is converted into an extremely large index according to the following formula:
wherein X represents a data set containing all measured values of the quality evaluation index, and X best Representing the best value in the data set X.
The interval index is converted into an extremely large index according to the following formula:
m = max { a-mix (X), max (X) -b } formula (3)
In the formula, a and b represent the lower and upper bounds of the optimal interval [ a, b ] in the data set X, and M represents the distance from the optimal interval.
The ultra-small index is converted into the ultra-large index according to the following formula:
the conversion of an extremely small index into an extremely large index will be described by taking the calculation of the consistency processing of the nuclear weight as an example.
The index value x' of the fresh litchi calculated by the formula (3) and the formula (4) to obtain the index value with the consistent quality evaluation index is shown in table 2.
TABLE 2 index values of consistent quality evaluation indexes of fresh litchi x '
Step 32 proceeds as follows: carrying out dimensionless processing on the standard value x' obtained after the index value x is subjected to the consistency processing to obtain a quality evaluation index standard value z of each group of quality evaluation indexes;
in the formula z m The standard value after the m-th quality evaluation index was normalized is shown.
The standard value z for the quality evaluation index of fresh litchi after the homogenization treatment and the dimensionless treatment is shown in table 3.
TABLE 3 Standard value z of standardized quality evaluation index of fresh litchi
And 4, step 4: calculating the contribution weight w of each group of quality evaluation indexes q Constructing quality evaluation for each quality evaluation categoryIndex weight matrix W g Calculating the contribution weight a of h quality evaluation categories g . Step 4 is performed by an Analytic Hierarchy Process (AHP), which means that elements related to the overall decision (the quality of the fresh litchi) are decomposed into a finished product quality evaluation target layer, a quality evaluation category layer, a quality evaluation index layer and the like, and then qualitative and quantitative analysis is performed. According to the quality evaluation target layer, the problem can be decomposed into different quality evaluation category layers and further into a quality evaluation index layer to form a multi-level analysis structure model, so that the problem is finally resolved into the determination of the relative important weight of the lowest layer relative to the highest layer or the arrangement of the relative good and bad order.
In the step 4, the over-analytic hierarchy process mainly comprises the following steps:
step 41: respectively selecting the relative importance of n quality evaluation indexes and h quality evaluation categories according to a scaling method (AHP), and respectively constructing a quality evaluation index judgment matrix B for each group of quality evaluation indexes g For each quality evaluation category, a quality evaluation category judgment matrix A is constructed g Constructing a quality evaluation index judgment matrix B g And a quality evaluation category judgment matrix A g Maximum eigenvalue λ of max And a consistency ratio CR, performing consistency check,
the judgment matrix is to compare any two indexes to obtain an importance result, and then present the result in a matrix form, wherein the difference of the importance degree adopts a scale method, and the grades are as follows:
TABLE 4 Scale of 1-9
| Scale | Means of |
| 1 | Represents the alpha index and the beta indexIn contrast, the two are equally important |
| 3 | Means that the former is slightly more important than the latter in comparison with the beta-th index |
| 5 | Means that the former is significantly more important than the latter in comparison with the beta-th index |
| 7 | Means that the former is more important than the latter in comparison with the alpha index |
| 9 | Means that the former is extremely important than the latter in comparison with the alpha- |
| 2、4、6、8 | Means that the importance of the first index to the second index is between two adjacent scales |
| Reciprocal of the | The importance of the alpha index compared with the beta index is b αβ The importance b of the beta index compared to the alpha index βα ＝1/b αβ |
Quality evaluation index judgment matrix B g Comprises the following steps:
in the formula, the element b 21 Is a quality evaluation index B 2 Compared with the quality evaluation index B 1 Is heavyEssential; n is the order number of the judgment matrix, namely the number of the quality evaluation indexes of each group, n =1,2,3 \8230,
the calculation formula for the consistency check is as follows:
in the formula, CI is a consistency index, RI is an average random consistency index, RI is an arithmetic mean obtained by repeatedly calculating a random judgment matrix eigenvalue for a plurality of times, and table 5 shows an average random consistency index obtained by repeatedly calculating a 1-10 dimensional matrix for 1000 times. The λ max can be calculated by mathab and other mathematical software.
TABLE 5 RI Tan
| n | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
| RI | 0 | 0 | 0.52 | 0.89 | 1.12 | 1.26 | 1.36 | 1.41 | 1.46 | 1.49 |
Comparing the consistency ratio CR with 0.1, and if CR is less than 0.1, passing consistency check; if CR is more than or equal to 0.1, the consistency test is not passed,
step 42: if the quality evaluation index judges the matrix B g Calculating a quality evaluation index judgment matrix B through consistency check g Maximum eigenvector and contribution weight w q Calculating a quality evaluation category judgment matrix A g Maximum eigenvector and contribution weight a g Then according to the contribution weight w q Constructing a quality evaluation index weight matrix W g (ii) a If the quality evaluation index judges the matrix B g If the consistency check is not passed, the step 41 is repeated until the quality evaluation index judgment matrix B is reached g And a quality evaluation category judgment matrix A g Through consistency check, the maximum feature vector can be calculated by mathematic software such as Matlab and the like.
Contribution weight w q The calculation formula is as follows:
in the formula, the contribution weight w q Represents the contribution weight of the q-th quality evaluation index, q =1,2 \8230n,
contribution weight a g Is calculated and the contribution weight w q In the same way, the first and second,
quality evaluation index weight matrix W g Comprises the following steps:
in the formula, a quality evaluation index weight matrix W g The weight matrix representing the g-th group of quality evaluation indexes, g =1,2 \8230, h.
According to the step 4, calculating each group of quality evaluation index layers, namely the contribution weight w of each quality evaluation category q And a contribution weight a for each quality evaluation category g Further, a quality evaluation index weight matrix W for each quality evaluation category is constructed g . The following is the contribution weight w for each quality evaluation category q And the contribution weight a of each quality evaluation category g The process of (2).
(1) Contribution weight w in relation to taste quality q Sum-quality evaluation index weight matrix W g
(1) Comparing the relative importance of soluble solid matter, sugar-acid ratio and total acid in pairs according to the 1-9 scaling method of Table 5, and constructing a judgment matrix B according to the formula (6) 1 Calculating the maximum eigenvalue and the maximum eigenvector corresponding to the maximum eigenvalue, and then calculating the judgment matrix B according to equations (7) and (8) and table 5 1 Comparing the consistency ratio with 0.1 to carry out consistency check, if the consistency check is not passed, reselecting the relative importance of the soluble solid matter, the sugar-acid ratio and the total acid to construct a new judgment matrix until the consistency check is passed, and finally obtaining a judgment matrix B which passes the consistency check 1 Comprises the following steps:
calculating to obtain a judgment matrix B 1 Maximum eigenvalue λ of max Is 3.0385, corresponding feature vectors are [0.1506,0.3715,0.9161] T ，
Referring to table 5, n takes values of 3, ri is 0.52, ci = (3.0385-3)/(3-1) =0.01925, cr =0.01925/0.52=0.037, less than 0.1, by consistency check,
(2) according to the judgment matrix B passing the consistency check 1 Constructing a weight matrix
w 1 ＝0.1506/(0.1506+0.3715+0.9161)＝0.105，
w 2 ＝0.3715/(0.1506+0.3715+0.9161)＝0.258，
w 3 ＝0.9161/(0.1506+0.3715+0.9161)＝0.637，
According to w 1 、w 2 、w 3 Constructing a weight matrix W 1 ，
(2) Contribution weight w with respect to process quality q Harmony evaluation index weight matrix W g
(1) Comparing the relative importance of juice yield, water content and nuclear weight pairwise according to the 1-9 scaling method of Table 5, and constructing a judgment matrix B according to the formula (6) 2 Calculating the maximum eigenvalue and the maximum eigenvector corresponding to the maximum eigenvalue, and then calculating the judgment matrix B according to equations (7) and (8) and table 5 2 Comparing the consistency ratio with 0.1 to carry out consistency check, if the consistency check is not passed, reselecting the relative importance of juice yield, moisture and nuclear weight to construct a new judgment matrix until the consistency check is passed, and finally obtaining a judgment matrix B which passes the consistency check 2 Comprises the following steps:
calculating outObtaining a judgment matrix B 2 Maximum eigenvalue λ of max Is 3.0246, the corresponding eigenvectors are [0.9471,0.1620,0.2769 ]] T ，
Referring to table 5, n takes the value of 3, ri is 0.52, ci = (3.0246-3)/(3-1) =0.0123, cr =0.0123/0.52=0.023, less than 0.1, by consistency check,
(2) according to the judgment matrix B passing the consistency test 2 Constructing a weight matrix
w 1 ＝0.9471/(0.9471+0.1620+0.2769)＝0.683，
w 2 ＝0.1620/(0.9471+0.1620+0.2769)＝0.117，
w 3 ＝0.2769/(0.9471+0.1620+0.2769)＝0.2，
According to w 1 、w 2 、w 3 Constructing a weight matrix W 2 ，
(3) Contribution weight w in respect of nutritional quality q Sum-quality evaluation index weight matrix W g
(1) The relative importance of total sugar, vitamins and proteins was compared pairwise according to the 1-9 scale of Table 5, and a decision matrix B was constructed with reference to equation (6) 3 Calculating the maximum eigenvalue and the maximum eigenvector corresponding to the maximum eigenvalue, and then calculating the judgment matrix B according to equations (7) and (8) and table 5 3 Comparing the consistency ratio with 0.1 to carry out consistency check, if the consistency check is not passed, reselecting the relative importance of total sugar, vitamins and proteins to construct a new judgment matrix until the consistency check is passed, and finally obtaining a judgment matrix B which passes the consistency check 3 Comprises the following steps:
calculating to obtain a judgment matrix B 2 Maximum eigenvalue λ of max Is 3.0385, corresponding characteristicThe eigenvectors are [0.9161,0.3715,0.1506] T ，
Referring to table 5, n values are 3, ri is 0.52, ci = (3.0385-3)/(3-1) =0.0123, cr =0.0123/0.52=0.037, less than 0.1, by consistency check,
(2) according to the judgment matrix B passing the consistency check 3 Constructing a weight matrix
w 1 ＝0.9161/(0.9161+0.3715+0.1506)＝0.637，
w 2 ＝0.3715/(0.9161+0.3715+0.1506)＝0.258，
w 3 ＝0.1506/(0.9161+0.3715+0.1506)＝0.105，
According to w 1 、w 2 、w 3 Constructing a weight matrix W 3 ，
(4) Contribution weight w with respect to quality of goods q Harmony evaluation index weight matrix W g
(1) Comparing the relative importance of edibility, single fruit weight and peel brightness according to scale 1-9 of Table 5, and constructing judgment matrix B according to formula (6) 4 Calculating the maximum eigenvalue and the maximum eigenvector corresponding to the maximum eigenvalue, and then calculating the judgment matrix B according to equations (7) and (8) and table 5 4 Comparing the consistency ratio with 0.1 to carry out consistency check, if the consistency check is not passed, reselecting the relative importance of the edibility rate, the weight of the single fruit and the brightness of the fruit peel to construct a new judgment matrix until the consistency check is passed, and finally obtaining a judgment matrix B which passes the consistency check 4 Comprises the following steps:
calculating to obtain a judgment matrix B 2 Maximum eigenvalue λ of max Is 3.0291, corresponding to feature vectors of [0.0908,0.2298,0.9690 ]] T ，
Referring to table 5, n values are 3, ri is 0.52, ci = (3.0291-3)/(3-1) =0.0123, cr =0.0123/0.52= -0.028, less than 0.1, by consistency check,
(2) according to the judgment matrix B passing the consistency check 3 Constructing a weight matrix
w 1 ＝0.0908/(0.0908+0.2298+0.9690)＝0.637，
w 2 ＝0.2298/(0.0908+0.2298+0.9690)＝0.258，
w 3 ＝0.9690/(0.0908+0.2298+0.9690)＝0.105，
According to w 1 、w 2 、w 3 Constructing a weight matrix W 4 ，
(5) Contribution weight a for a fresh litchi sample q
(1) Comparing the relative importance of taste quality, processing quality, nutrition quality and commodity quality according to scale 1-9 of Table 5, and constructing judgment matrix A with reference to formula (6) g Calculating the maximum eigenvalue and the maximum eigenvector corresponding to the maximum eigenvalue, and then calculating the judgment matrix B according to equations (7) and (8) and table 5 4 Comparing the consistency ratio with 0.1 to carry out consistency check, if the consistency check is not passed, reselecting the relative importance of the edibility rate, the weight of the single fruit and the brightness of the fruit peel to construct a new judgment matrix until the consistency check is passed, and finally obtaining a judgment matrix A passing the consistency check g Comprises the following steps:
calculating to obtain a judgment matrix A g Maximum eigenvalue λ of max At 4.1776, the corresponding feature vectors are [0.8851,0.0815,0.2015,0.4114 ]] T ，
Referring to table 5, n takes on a value of 4, ri is 0.89, ci = (4.1776-4)/(4-1) =0.0592, cr =/0.89=0.07, less than 0.1, by consistency check,
(2) according to the judgment matrix A passing the consistency test g Calculating to obtain contribution weight a g
a 1 ＝0.8851/(0.8851+0.0815+0.2015+0.4114)＝0.56，
a 2 ＝0.0815/(0.8851+0.0815+0.2015+0.4114)＝0.052，
a 3 ＝0.2015/(0.8851+0.0815+0.2015+0.4114)＝0.128，
a 4 ＝0.4114/(0.8851+0.0815+0.2015+0.4114)＝0.26，
And 5: calculating a score value H of each quality evaluation category p-g . And step 5, a TOPSIS method, also called an ideal solution method, is an effective multi-index evaluation method. The method and the principle are as follows: firstly, setting a multi-attribute decision scheme set as D = { D11, D2., dm } D = { D11, D2.,. Dm }, wherein variables for measuring the quality of the scheme attributes are x1, · ·, xn, x1, ·, xn, and vectors formed by nn attribute values of each scheme of the scheme D are [ ai1, ·, ain }, and D]，[ai1，···，ain]As a point in the nn-dimensional space, it uniquely represents a certain scheme. And constructing a positive ideal solution and a negative ideal solution, wherein the attribute value of C0 is the optimal/inferior value of the attribute in the decision matrix. In an nn-dimensional space, comparing the distances between the solutions in the solution set DD and C0, the solution close to the positive ideal solution and far from the negative ideal solution is the optimal solution. The step 5 comprises the following steps:
step 51: constructing a quality evaluation index initial evaluation matrix E according to the standard value x of each group of quality evaluation indexes g ，
Initial evaluation matrix E of quality evaluation index g Comprises the following steps:
in the formula, an initial evaluation matrix E of quality evaluation indexes g Representing the initial evaluation matrix of the g group quality evaluation index; m represents the number of fresh litchi samples, n represents the quality evaluationThe number of price indices; element e mn Quality evaluation index standard value x for expressing n indexes of mth fresh litchi sample mn ，
Step 52: initial evaluation matrix E combined with quality evaluation indexes g And a quality evaluation index weight matrix W g Constructing a quality evaluation index weighted evaluation matrix K g ，
Quality evaluation index weighted evaluation matrix K g The calculation formula of (2) is as follows:
in the formula, K g A weighted evaluation matrix representing the g-th group of quality evaluation indexes, m represents the number of fresh litchi samples, n represents the number of the quality evaluation indexes,
step 53: determining a quality evaluation index weighted evaluation matrix K g Optimal solution K of q + And worst solution K q - Calculating the p-th fresh litchi sample and the optimal solution K q + Euclidean distance k of q + Calculating the p-th fresh eating litchi sample and the worst solution K q - Euclidean distance k of q - ，p＝1，2，3....m，q＝1，2，3...n，
K g + ＝[k 1 + ，k 2 + ，...，k n + ]＝[max(k 11 ，k 21 ，...，k m1 )，max(k 12 ，k 22 ，...，k m2 )，...，max(k 1n ，k 2n ，...，k mn )]Formula (13)
K g - ＝[k 1 - ，k 2 - ，...，K n - ]＝[min(k 11 ，k 21 ，...，k m1 )，min(k 12 ，k 22 ，...，k m2 )，...，min(k 1n ，k 2n ，...，k mn )]Formula (14)
Optimal solution K q + For quality evaluationPrice index weighted evaluation matrix K g The set of the maximum values of the corresponding elements under the n quality evaluation indexes of the medium m fresh eating litchi samples, the worst solution K q - Weighting the evaluation matrix K for the quality evaluation index g The minimum value set of the n quality evaluation indexes of the medium m fresh eating litchi samples,
in the formula, k pq A weighting standard value, k, of the q-th quality evaluation index of the p-th fresh litchi sample pq - A weighting standard value, k, of the q-th quality evaluation index of the p-th fresh litchi sample q + 、k q - Respectively represents K q + And K q - The maximum and minimum values of the qth index in the m samples, p =1,2,3.. M, q =1,2,3 \8230n,
step 54: according to Euclidean distance k p + 、k p - Calculating the score value H of the quality evaluation category p-g ，
In the formula, H p-g The score values of the g-th quality evaluation category of the p-th fresh litchi sample are represented, wherein p =1,2,3 \8230m, g =1,2,3.. H.
(1) Initial evaluation matrix E for taste quality 1 And a weighted evaluation matrix K 1
(1) According to the standard values of soluble solid, sugar-acid ratio and total acid in the quality evaluation indexes of the fresh litchi in the table 1, an initial evaluation matrix E of the taste quality is constructed 1 The following were used:
(2) initial evaluation matrix E combined with quality evaluation indexes 1 And a quality evaluation index weight matrix W 1 Constructing a quality evaluation index weighted evaluation matrix K 1 The following were used:
(3) determining a quality evaluation index weighted evaluation matrix K 1 Optimal solution K of 1 + And worst solution K 1 - Comprises the following steps:
| k +: maximum value of evaluation index value | 0.0335 | 0.0890 | 0.2617 |
| k-: minimum value of evaluation index value | 0.0252 | 0.0000 | 0.0864 |
According to the formulas (15) and (16), calculating the 1 st fresh litchi sample and the optimal solution K 1 + Euclidean distance k of 1 + Calculating the 1 st fresh litchi sample and the worst solution K g - Euclidean distance k of p - ，
Taste quality X of 2-12 fresh eating litchi samples p-g Reference may be made to the above calculation process.
(4) According to the formulas (16) to (18), the fresh litchi score value H of each sample based on the taste quality is obtained 1-1 -H 12-1 As shown in table 6.
(2) Initial evaluation matrix E for processing quality 2 And a weighted evaluation matrix K 2
(1) According to standard values of juice yield, water content and kernel weight in the quality evaluation indexes of the fresh litchi in the table 1, an initial evaluation matrix E of the taste quality is constructed 2 The following were used:
(2) initial evaluation matrix E combined with quality evaluation indexes 2 And a quality evaluation index weight matrix W 2 Constructing a quality evaluation index weighted evaluation matrix K 2 The following were used:
(3) determining a quality evaluation index weighted evaluation matrix K 2 Of (2) an optimal solution K 2 + And worst solution K 2 - Comprises the following steps:
| k +: maximum value of evaluation index value | 0.2273 | 0.0394 | 0.0806 |
| k-: minimum value of evaluation index value | 0.1525 | 0.0280 | 0.0364 |
According to the formulas (15) and (16), calculating the 1 st fresh litchi sample and the optimal solution K 2 + Euclidean distance k of 2 + Calculating the 1 st fresh litchi sample and the worst solution K g - Euclidean distance k of p - ，
H of processing quality of 2-12 fresh eating litchi samples p-g Reference may be made to the above calculation process.
(4) According to the formulas (16) to (18), the fresh litchi score value H of each sample based on the taste quality is obtained 1-2 -H 12-2 As shown in table 6.
(3) Initial evaluation matrix E for nutritional quality 3 And a weighted evaluation matrix K 3
(1) According to the standard values of total sugar, vitamins and protein in the quality evaluation indexes of the fresh litchi in the table 1, an initial evaluation matrix E of the taste quality is constructed 3 The following were used:
(2) initial evaluation matrix E combined with quality evaluation indexes 3 And a quality evaluation index weight matrix W 3 Constructing a quality evaluation index weighted evaluation matrix K 3 The following were used:
(3) determining a quality evaluation index weighted evaluation matrix K 3 Optimal solution K of 3 + And worst solution K 3 - Comprises the following steps:
| k +: maximum value of evaluation index value | 0.2254 | 0.1435 | 0.0245 |
| k-: minimum value of evaluation index value | 0.1455 | 0.0345 | 0.0013 |
According to the formulas (15) and (16), calculating the 1 st fresh litchi sample and the optimal solution K 3 + Euclidean distance k of 3 + Calculating the 1 st fresh litchi sample and the worst K g - Euclidean distance k of p - ，
H of nutrition quality of 2-12 fresh eating litchi samples p-g Reference may be made to the above calculation process.
(4) According to the formulas (16) to (18), the fresh litchi score value H of each sample based on the taste quality is obtained 1-3 -H 12-3 As shown in table 6.
(4) Initial evaluation matrix E for commodity quality 4 And a weighted evaluation matrix K 4
(1) According to the standard values of the edibility, the weight of a single fruit and the brightness of peel in the quality evaluation indexes of the fresh litchi in the table 1, an initial evaluation matrix E of the taste quality is constructed 4 The following:
(2) initial evaluation matrix E combined with quality evaluation indexes 4 And a quality evaluation index weight matrix W 4 Constructing a quality evaluation index weighted evaluation matrix K 4 The following:
(3) determining a quality evaluation index weighted evaluation matrix K 4 Of (2) an optimal solution K 4 + And worst solution K 4 - Comprises the following steps:
| k +: maximum value of evaluation index value | 0.0245 | 0.0880 | 0.2351 |
| k-: minimum value of evaluation index value | 0.0165 | 0.0362 | 0.1854 |
According to the formulas (15) and (16), calculating the 1 st fresh litchi sample and the optimal solution K 4 + Euclidean distance k of 4 + Calculating the 1 st fresh litchi sample and the worst solution K g - Euclidean distance k of p - ，
H of commodity quality of 2 th to 12 th fresh eating litchi samples p-g Reference may be made to the above calculation process.
(4) According to the formulas (16) to (18), the fresh litchi score value H of each sample based on the taste quality is obtained 1-4 -H 12-4 As shown in table 6.
Table 6 fresh eating litchi score value H of each fresh eating litchi sample based on quality evaluation category p-g
Step 6: according to the contribution weight a g And a score value H p-g Calculating the comprehensive score Y of each fresh litchi sample p ；
And 7: according to a composite score Y p Comparing and sequencing the quality of the m fresh litchi samples, determining the quality grade of the m fresh litchi samples, and comprehensively scoring Y p The larger the sample, the better the quality of the fresh litchi sample.
According to one embodiment of the invention, step 6 comprises:
calculating a composite score Y according to the following calculation formula p ，
In the formula Y p Represents the comprehensive score of the pth fresh litchi sample, and p =1,2,3 \8230h, m, g =1,2,3 \8230h.
The contribution weight of each quality category to the evaluation of the quality of fresh litchi and the evaluation value of each quality category are integrated, and the integrated scores of the litchi 1-litchi 12 samples calculated according to the formula (19) are shown in Table 7
TABLE 7 comprehensive score Y of fresh litchi samples p
| m | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 |
| Y p | 0.2814 | 0.4452 | 0.4867 | 0.5201 | 0.3628 | 0.5536 | 0.5474 | 0.4700 | 0.6958 | 0.5620 | 0.6012 | 0.5984 |
And sequencing the comprehensive scores of the litchi 1-litchi 12 samples to obtain the optimal comprehensive quality of the litchi 9 sample.
The foregoing description of specific embodiments has been presented for purposes of illustration and description. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multi-step processing and parallel processing are also possible or may be advantageous.
It is intended that the one or more embodiments of the present specification embrace all such alternatives, modifications and variations as fall within the broad scope of the appended claims. Therefore, any omissions, modifications, substitutions, improvements, and the like that may be made without departing from the spirit or scope of the disclosure are intended to be included within the scope of the disclosure.
Claims (7)
1. A method for comprehensively evaluating the quality of fresh litchi comprises the following steps:
step 1: determining fresh litchi samples according to the production area and variety of fresh litchi, wherein the number of the fresh litchi samples is m, m =1,2,3,4,5 \8230;
step 2: establishing a three-level quality evaluation system of the fresh litchi quality comprehensive evaluation, wherein the three-level index evaluation system of the fresh litchi quality comprehensive evaluation comprises a quality evaluation index layer, a quality evaluation category layer and a quality evaluation target layer from bottom to top, the quality evaluation category layer comprises h quality evaluation categories, the quality evaluation index layer comprises h groups of quality evaluation indexes, the number of the quality evaluation indexes in each group is n, each quality evaluation category comprises a group of the quality evaluation indexes, the quality evaluation target layer is m fresh litchi samples, h =1,2,3,4,5 \ 8230, n =1, 3,4,5 \ 8230and a \ 8230;
and step 3: measuring an index value x of each group of the quality evaluation indexes, and carrying out data standardization on the index value x to obtain a quality evaluation index standard value z of each group of the quality evaluation indexes:
and 4, step 4: calculating the contribution weight w of each group of the quality evaluation indexes q Constructing a quality evaluation index weight matrix W for each quality evaluation category g Calculating the contribution weight a of h quality evaluation categories g ；
And 5: calculating a score value H for each of the quality-assessment categories p-g ；
Step 6: according to the contribution weight a g And the score value H p-g ComputingComprehensive score Y of each fresh litchi sample p ；
And 7: according to the comprehensive score Y p Comparing and sequencing the quality of the m fresh litchi samples, determining the quality grade of the m fresh litchi samples, and comprehensively scoring Y p The larger the sample, the better the quality of the fresh litchi sample.
2. The method of claim 1, wherein the quality evaluation categories of the quality evaluation category layer include, but are not limited to, taste quality, processing quality, nutritional quality, commodity quality, storage and transportation quality.
3. The method for comprehensively evaluating the quality of fresh litchi as claimed in claim 2, wherein the quality evaluation indexes of the taste quality include but are not limited to soluble solids, sugar-acid ratio, pH, total acid, organic acid; the quality evaluation indexes of the processing quality include, but are not limited to, juice yield, moisture, nuclear weight and ash content; the quality evaluation indexes of the nutritional quality include but are not limited to total sugar, vitamins, protein, amino acid and fat; the quality evaluation indexes of the commodity quality include but are not limited to edibility, single fruit weight, peel brightness and defective fruit; the storage and transportation quality includes, but is not limited to, preservation performance during storage, preservation performance during transportation, and preservation performance during shelf life.
4. The method for comprehensively evaluating the quality of fresh litchi as claimed in claim 1, wherein the step 3 comprises:
step 31: measuring an index value x for each set of quality evaluation indexes, performing a matching process on the index values x for each set of quality evaluation indexes,
classifying the n quality evaluation indexes into an intermediate index, an interval index and an ultra-small index according to the preferred values of the quality evaluation indexes, and then respectively converting the intermediate index, the interval index and the ultra-small index into an ultra-large index, wherein,
the intermediate index is converted into an extremely large index according to the following formula:
in the formula, x m ' represents an index value, x, of the mth fresh litchi sample after conversion of some quality evaluation index m Indicating the index value of the mth fresh litchi sample before the transformation of the quality evaluation index, X indicating the data set containing all measured values of the quality evaluation index, and X best Represents the best value in the data set X,
the interval type index is converted into an extremely large index according to the following formula:
m = max { a-mix (X), max (X) -b } formula (3)
Wherein a, b represent the lower and upper bounds of an optimal interval [ a, b ] in the data set X, M represents the distance from the optimal interval,
the ultra-small index is converted into an ultra-large index according to the following formula:
step 32: carrying out dimensionless processing on the data obtained by carrying out the index value x in a consistent manner to obtain a quality evaluation index standard value z of each group of quality evaluation indexes;
in the formula z m Shows the m-th quality evaluation index after normalizationThe standard value of (2).
5. The method for comprehensively evaluating the quality of fresh litchi as claimed in claim 1, wherein the step 4 comprises:
step 41: respectively selecting the relative importance of the n quality evaluation indexes and the h quality evaluation categories according to a scaling method, and respectively constructing the quality evaluation index judgment matrix B for each group of the quality evaluation indexes g Constructing the quality evaluation category judgment matrix A for each quality evaluation category g Calculating the quality evaluation index judgment matrix B g And the quality evaluation type judgment matrix A g Maximum eigenvalue λ of max And a consistency ratio CR, carrying out consistency check,
the quality evaluation index judgment matrix B g Comprises the following steps:
in the formula, the element b 21 Is the quality evaluation index B 2 Compared with the quality evaluation index B 1 The importance of (c); n is the order of the judgment matrix, namely the number of the quality evaluation indexes in each group, n =1,2,3 \ 8230,
the calculation formula of the consistency test is as follows:
wherein CI is a consistency index, RI is an average random consistency index,
comparing the consistency ratio CR with 0.1, and if CR is less than 0.1, passing consistency test; if CR is more than or equal to 0.1, the consistency test is not passed,
step 42: if the quality evaluation index judgment matrix Bg passes the consistency test, calculating the quality evaluation index judgment matrix B g And the contribution weight w q Calculating the quality evaluation category judgment matrix Ag And the contribution weight a g Then according to said contribution weight w q Constructing a quality evaluation index weight matrix W of the product g ；
If the quality evaluation index judgment matrix B g If the consistency check is not passed, the step 41 is repeated until the quality evaluation index judgment matrix B is reached g And the quality evaluation category judgment matrix A g By means of the consistency check, it is possible to check for consistency,
the contribution weight w q The calculation formula is as follows:
in the formula, the contribution weight w q Represents the contribution weight of the q-th quality evaluation index, q =1,2 \8230n,
the contribution weight a g And the contribution weight w q In the same way, the first and second,
the quality evaluation index weight matrix W g Comprises the following steps:
wherein the quality evaluation index weight matrix W g The weight matrix representing the quality evaluation index of group g, g =1,2 \8230;, h.
6. The method for comprehensively evaluating the quality of fresh litchi as claimed in claim 1, wherein the step 5 comprises:
step 51: according to the standard value x of each group of the quality evaluation indexesEstablishing a quality evaluation index initial evaluation matrix E g ，
The initial evaluation matrix E of the quality evaluation index g Comprises the following steps:
in the formula, an initial evaluation matrix E of quality evaluation indexes g Representing the initial evaluation matrix of the quality evaluation index of the g group; m represents the number of the fresh litchi samples, and n represents the number of the quality evaluation indexes; element e mn The quality evaluation index standard value x representing n indexes of the mth fresh litchi sample mn ，
Step 52: combining the quality evaluation index initial evaluation matrix E g And the quality evaluation index weight matrix W g Constructing a quality evaluation index weighted evaluation matrix K g ，
The quality evaluation index weighted evaluation matrix K g The calculation formula of (2) is as follows:
in the formula, K g A weighted evaluation matrix representing the g-th group of the quality evaluation indexes, m representing the number of the fresh litchi samples, n representing the number of the quality evaluation indexes,
step 53: determining the quality evaluation index weighted evaluation matrix K g Of (2) an optimal solution K q + And worst solution K q - Calculating the pth fresh litchi sample and the optimal solution K q + Euclidean distance k of q + Calculating the pth fresh litchi sample and the worst solution K q - Euclidean distance k of q - ，p＝1，2，3…m，q＝1，2，3…n，
K g + ＝[k 1 + ，k 2 + ，...，k n + ]＝[max(k 11 ，k 21 ，...，k m1 )，max(k 12 ，k 22 ，...，k m2 )，...，max(k 1n ，k 2n ，...，k mn )]Formula (13)
K g - ＝[k 1 - ，k 2 - ，...，k n - ]＝[min(k 11 ，k 21 ，...，k m1 )，min(k 12 ，k 22 ，...，k m2 )，...，min(k 1n ，k 2n ，...，k mn )]Formula (14)
The optimal solution K q + Weighting the quality evaluation index by an evaluation matrix K g The set of the maximum values of the corresponding elements under the n quality evaluation indexes of the medium m fresh litchi samples, and the worst solution K q - Weighting the quality evaluation index by an evaluation matrix K g The minimum value set of the n quality evaluation indexes of the medium m fresh eating litchi samples,
in the formula, k pq A weighting standard value k representing the q-th quality evaluation index of the p-th fresh litchi sample pq - A weighting standard value, k, of the q-th quality evaluation index of the p-th fresh litchi sample q + 、k q - Respectively represents K q + And K q - The maximum and minimum values of the qth index in the m samples, p =1,2,3 \ 8230m, q =1,2,3 \ 8230n,
step 54: according to the Euclidean distance k p + 、k p - Calculating a score value H of the quality evaluation category p-g ，
In the formula, H p-g The score values of the g-th quality evaluation category of the p-th fresh litchi sample are represented, wherein p =1,2,3 8230h, m, g =1,2,3 8230h.
7. The method for comprehensive evaluation of the quality of fresh litchi as claimed in claim, wherein said step 6 comprises:
calculating the composite score Y according to the following calculation formula p ，
In the formula Y p Represents the comprehensive score of the pth fresh litchi sample, and p =1,2,3 \ 8230h, m, g =1,2,3 \ 8230h.
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